Chief Data Strategist

6 days ago


Baltimore, Maryland, United States Aegistech Full time

Aegistech Seeks Expert Lead Data Scientist

As a key member of our Data Science & Analytics team, you will play a crucial role in pushing the boundaries of our analytics and predictive capabilities. With a strong focus on research, experimentation, and data modeling techniques, you will work closely with our team to develop and implement advanced & predictive analytics solutions that drive business growth and margin.

Key Responsibilities:

  • Exposing Insights: Turn data into actionable information by producing analysis reports and diagnostic models to uncover hidden relationships and patterns between our data and key metrics.
  • Evaluate & Produce Quality: Ensure high-quality code by reviewing your own and your teammates' code, ensuring it is free from errors, bias, and easy to understand.
  • Data Engineering: Gather, clean, and preprocess data from various sources, performing feature engineering to improve dataset quality and usefulness. Deploy pipelines on cloud-based infrastructure.
  • Predictive Modeling: Develop, validate, and deploy predictive models using machine learning algorithms and statistical techniques, such as regression, classification, clustering, time series forecasting, and optimization.
  • Generative Modeling: Utilize open-source and paid technologies to produce abstractions and novel features for other applications.
  • Continuous Improvement: Stay up-to-date with the latest developments in data science, machine learning, and reporting technologies, contributing to knowledge-sharing sessions to grow and develop others.
Required Skills and Qualifications
  • 6+ years of experience in data science or machine learning roles.
  • Familiarity with business efficiency metrics, including Customer Acquisition Cost (CAC), Revenue Acquisition Cost (RAC), Retention, Margin, Annual Recurring Revenue (ARR), Lifetime Value (LTV), and Engagement.
  • Experience with at least one dashboarding tool, such as Tableau, Power BI, Looker, Google Data Studio, Streamlit, Dash, etc.
  • Proficiency with Python and SQL.
  • Knowledge of machine learning algorithms and statistical techniques for predictive modeling, including Regression, Classification, Clustering, Time Series Analysis, and Optimization.
  • Proficiency with end-to-end pipelines.
  • Expert knowledge in model evaluation metrics.
  • Experience pulling data from various third-party systems and APIs.
  • Proficiency with version control.
  • Proven ability to work both independently and as part of a team.
  • Proficiency with visualization in Python.
  • Familiarity with best practices in secure data handling and customer data privacy.
Benefits
  • $120,000 - $180,000 annual salary depending on location and experience.
  • Flexible PTO.
  • All benefits: medical, dental, and vision insurance, 401(k) with employer match, short- and long-term disability coverage, life insurance options, and paid parental leave.
  • Certification reimbursement program.
  • Work from anywhere in the US.


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